System, method, and computer program product for predicting a specified geographic area of a user

Abstract

Provided is a system, method, and computer program product for predicting a specified geographic area of a user. The method includes receiving transaction data associated with a plurality of transactions during a predetermined time interval. The method also includes generating a geographic area prediction model based on the transaction data by determining a verified geographic area for each user, and determining transaction data associated with a plurality of transactions involving each user for a plurality of feature vector parameters, training the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user, and validating the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user.

The invention claimed is: 
     
       1. A method, comprising:
 receiving, with at least one processor, transaction data associated with a plurality of transactions involving a plurality of users and a plurality of merchants during a predetermined time interval; 
 generating, with at least one processor, a geographic area prediction model; 
 determining, with at least one processor, a verified geographic area of a plurality of geographic areas for each user of the plurality of users; 
 determining, with at least one processor, transaction data associated with a plurality of transactions involving each user of the plurality of users for each feature vector parameter of a plurality of feature vector parameters, wherein determining the transaction data comprises determining each feature vector parameter of the plurality of feature vector parameters for each geographic area of the plurality of geographic areas; 
 training, with at least one processor, the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user of the plurality of users; 
 validating, with at least one processor, the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user of the plurality of users; and 
 repeating over a plurality of time intervals:
 generating, with at least one processor, a prediction that a user will conduct a transaction in a geographic area based on the geographic area prediction model; 
 communicating, with at least one processor, an offer to the user based on the prediction; 
 receiving, with at least one processor, new training data by processing a transaction conducted by the user in the geographic area within a predetermined amount of time from the offer being communicated to the user; and 
 updating, with at least one processor, the geographic area prediction model based on the new training data. 
 
 
     
     
       2. The method of  claim 1 , wherein determining each feature vector parameter of the plurality of feature vector parameters for each geographic area of the plurality of geographic areas comprises:
 identifying a plurality of feature vector parameters associated with the verified geographic area for each user of the plurality of users; and 
 excluding a plurality of feature vector parameters associated with each geographic area of the plurality of geographic areas that does not correspond to the verified geographic area. 
 
     
     
       3. The method of  claim 1 , further comprising:
 receiving first transaction data associated with a plurality of first transactions involving a first user of the plurality of users; 
 determining a plurality of feature vector parameters for each geographic area of the plurality of geographic areas based on the first transaction data associated with the plurality of first transactions; and 
 based on the geographic area prediction model and the plurality of feature vector parameters for the verified geographic area of the first user, assigning a predicted geographic area to the first user. 
 
     
     
       4. The method of  claim 3 , further comprising assigning the predicted geographic area of the first user to a debit account associated with the first user. 
     
     
       5. The method of  claim 3 , further comprising:
 determining, based on the first transaction data associated with a plurality of first transactions involving the first user, second transaction data associated with a second plurality of transactions involving the first user and a first plurality of merchants of the plurality of merchants in the predicted geographic area of the first user; and 
 determining a geographic location of the first user in the predicted geographic area of the first user associated with a position of the first plurality of merchants based on the second transaction data associated with the second plurality of transactions. 
 
     
     
       6. The method of  claim 5 , wherein the geographic location of the first user in the predicted geographic area of the first user is associated with at least one geographic coordinate, wherein the at least one geographic coordinate comprises a latitude coordinate, a longitude coordinate, or any combination thereof. 
     
     
       7. The method of  claim 5 , further comprising determining a geographic location of each of the first plurality of merchants, wherein the geographic location of the user in the predicted geographic area of the user corresponds to a central position associated with the position of the first plurality of merchants. 
     
     
       8. The method of  claim 1 , wherein the transaction data associated with the plurality of transactions comprises credit card transaction data associated with a plurality of credit card payment transactions and the verified geographic area comprises a credit card billing geographic area. 
     
     
       9. The method of  claim 1 , wherein the geographic area comprises a zip code and wherein the verified geographic area comprises a billing zip code associated with an account of a user. 
     
     
       10. The method of  claim 1 , wherein the plurality of feature vector parameters comprises at least one of the following:
 a maximum number of transactions involving a user in a maximum merchant category of a plurality of merchant categories; 
 a transaction amount associated with the maximum number of transactions involving a user in the maximum merchant category of the plurality of merchant categories; 
 a time of day associated with the maximum number of transactions in the maximum merchant category of the plurality of merchant categories; 
 a day of a week associated with the maximum number of transactions in the maximum merchant category of the plurality of merchant categories; 
 a transaction amount associated with a plurality of transactions in the maximum merchant category in the plurality of geographic areas; 
 a transaction amount associated with a plurality of transactions in at least one of the following merchant categories:
 a merchant category associated with fuel, 
 a merchant category associated with dry cleaning, 
 a merchant category associated with laundry, 
 a merchant category associated with mail, 
 a merchant category associated with video rental, 
 a merchant category associated with grocery, 
 a merchant category associated with miscellaneous food sales, 
 a merchant category associated with restaurant, 
 a merchant category associated with quick service restaurant (QSR), or 
 any combination thereof; 
 
 a transaction amount associated with a plurality of transactions during a weekday of a week in a merchant category associated with restaurant, a merchant category associated with QSR, or any combination thereof; 
 a transaction amount associated with a plurality of transactions during a weekend day of a week in a merchant category associated with restaurant, a merchant category associated with QSR, or any combination thereof; 
 a time of day associated with at least one transaction in a merchant category of the plurality of merchant categories; 
 a day of a week associated with at least one transaction in a merchant category of the plurality of merchant categories; 
 a transaction amount associated with a plurality of transactions in each of the plurality of merchant categories in a geographic area; 
 a transaction amount associated with a plurality of transactions in the plurality of merchant categories in a geographic area; or 
 any combination thereof. 
 
     
     
       11. A system comprising at least one server computer including at least one processor, the at least one server computer programmed and/or configured to:
 receive transaction data associated with a plurality of transactions involving a plurality of users and a plurality of merchants during a predetermined time interval; 
 generate a geographic area prediction model; 
 determine a verified geographic area of a plurality of geographic areas for each user of the plurality of users; 
 determine transaction data associated with a plurality of transactions involving each user of the plurality of users for each feature vector parameter of a plurality of feature vector parameters, wherein determining the transaction data comprises determining each feature vector parameter of the plurality of feature vector parameters for each geographic area of the plurality of geographic areas; 
 train the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user of the plurality of users; 
 validate the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user of the plurality of users; and 
 repeat over a plurality of time intervals:
 generate a prediction that a user will conduct a transaction in a geographic area based on the geographic area prediction model; 
 communicate an offer to the user based on the prediction; 
 receive new training data by processing a transaction conducted by the user in the geographic area within a predetermined amount of time from the offer being communicated to the user; and 
 update the geographic area prediction model based on the new training data. 
 
 
     
     
       12. The system of  claim 11 , wherein determining each feature vector parameter of the plurality of feature vector parameters for each geographic area of the plurality of geographic areas comprises:
 identifying a plurality of feature vector parameters associated with the verified geographic area for each user of the plurality of users; and 
 excluding a plurality of feature vector parameters associated with each geographic area of the plurality of geographic areas that does not correspond to the verified geographic area. 
 
     
     
       13. The system of  claim 11 , wherein the at least one server computer is further programmed and/or configured to:
 receive first transaction data associated with a plurality of first transactions involving a first user of the plurality of users; 
 determine a plurality of feature vector parameters for each geographic area of the plurality of geographic areas based on the first transaction data associated with the plurality of first transactions; and 
 based on the geographic area prediction model and the plurality of feature vector parameters for the verified geographic area of the first user, assign a predicted geographic area to the first user. 
 
     
     
       14. The system of  claim 13 , wherein the at least one server computer is further programmed and/or configured to assign the predicted geographic area of the first user to a debit account associated with the first user. 
     
     
       15. The system of  claim 13 , wherein the at least one server computer is further programmed and/or configured to:
 determine, based on the first transaction data associated with a plurality of first transactions involving the first user, second transaction data associated with a second plurality of transactions involving the first user and a first plurality of merchants of the plurality of merchants in the predicted geographic area of the first user; and 
 determine a geographic location of the first user in the predicted geographic area of the first user associated with a position of the first plurality of merchants based on the second transaction data associated with the second plurality of transactions. 
 
     
     
       16. The system of  claim 15 , wherein the geographic location of the first user in the predicted geographic area of the first user is associated with at least one geographic coordinate, wherein the at least one geographic coordinate comprises a latitude coordinate, a longitude coordinate, or any combination thereof. 
     
     
       17. The system of  claim 15 , wherein the at least one server computer is further programmed and/or configured to determine a geographic location of each of the first plurality of merchants, wherein the geographic location of the user in the predicted geographic area of the user corresponds to a central position associated with the position of the first plurality of merchants. 
     
     
       18. The system of  claim 11 , wherein the transaction data associated with the plurality of transactions comprises credit card transaction data associated with a plurality of credit card payment transactions and the verified geographic area comprises a credit card billing geographic area. 
     
     
       19. The system of  claim 11 , wherein the geographic area comprises a zip code and wherein the verified geographic area comprises a billing zip code associated with an account of a user. 
     
     
       20. A computer program product comprising at least one non-transitory computer-readable medium including program instructions that, when executed by at least one processor, cause the at least one processor to:
 receive transaction data associated with a plurality of transactions involving a plurality of users and a plurality of merchants during a predetermined time interval; 
 generate a geographic area prediction model; 
 determine a verified geographic area of a plurality of geographic areas for each user of the plurality of users; 
 determine transaction data associated with a plurality of transactions involving each user of the plurality of users for each feature vector parameter of a plurality of feature vector parameters, wherein determining the transaction data comprises determining each feature vector parameter of the plurality of feature vector parameters for each geographic area of the plurality of geographic areas; 
 train the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user of the plurality of users; 
 validate the geographic area prediction model based on the plurality of feature vector parameters for the verified geographic area for each user of the plurality of users; and 
 repeat over a plurality of time intervals:
 generate a prediction that a user will conduct a transaction in a geographic area based on the geographic area prediction model; 
 communicate an offer to the user based on the prediction; 
 receive new training data by processing a transaction conducted by the user in the geographic area within a predetermined amount of time from the offer being communicated to the user; and 
 update the geographic area prediction model based on the new training data.